Generalized Feature Embedding for Supervised, Unsupervised, and Online Learning Tasks
Sign Up to like & getrecommendations! Published in 2019 at "Information Systems Frontiers"
DOI: 10.1007/s10796-018-9850-y
Abstract: Feature embedding is an emerging research area which intends to transform features from the original space into a new space to support effective learning. Many feature embedding algorithms exist, but they often suffer from several… read more here.
Keywords: supervised unsupervised; learning tasks; feature; online learning ... See more keywords
The Perceived Complexity of Learning Tasks Influences Students’ Collaborative Interactions in Immersive Virtual Reality
Sign Up to like & getrecommendations! Published in 2024 at "Journal of Science Education and Technology"
DOI: 10.1007/s10956-024-10103-1
Abstract: This study investigated how different learning tasks influence students’ collaborative interactions in immersive Virtual Reality (iVR). A set of chemistry learning activities was designed with iVR, and 35 pairs of undergraduate students went through the… read more here.
Keywords: learning tasks; students collaborative; collaborative interactions; interactions immersive ... See more keywords
Word learning tasks as a window into the triggering problem for presuppositions
Sign Up to like & getrecommendations! Published in 2024 at "Natural Language Semantics"
DOI: 10.1007/s11050-024-09224-5
Abstract: In this paper, we show that native speakers spontaneously divide the complex meaning of a new word into a presuppositional component and an assertive component. These results argue for the existence of a productive triggering… read more here.
Keywords: learning tasks; window triggering; word; word learning ... See more keywords
A Specific Implicit Sequence Learning Deficit as an Underlying Cause of Dyslexia? Investigating the Role of Attention in Implicit Learning Tasks
Sign Up to like & getrecommendations! Published in 2017 at "Neuropsychology"
DOI: 10.1037/neu0000348
Abstract: Objective: Recently, a general implicit sequence learning deficit was proposed as an underlying cause of dyslexia. This new hypothesis was investigated in the present study by including a number of methodological improvements, for example, the… read more here.
Keywords: implicit learning; learning tasks; sequence learning; implicit sequence ... See more keywords
Efficient Spiking Variational Graph Autoencoders for Unsupervised Graph Representation Learning Tasks
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Intelligent Systems"
DOI: 10.1109/mis.2024.3391937
Abstract: Variational graph autoencoders (VGAEs) are popular artificial neural network (ANN)-based models for unsupervised graph representation learning tasks, including link prediction and graph generation, which are critical in many real-world applications. Despite the promising results of… read more here.
Keywords: learning tasks; graph autoencoders; graph representation; variational graph ... See more keywords
Causality-Aware Predictions in Static Anticausal Machine Learning Tasks.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3202151
Abstract: We propose a counterfactual approach to train "causality-aware" predictive models that are able to leverage causal information in static anticausal machine learning tasks (i.e., prediction tasks where the outcome influences the inputs). In applications plagued… read more here.
Keywords: static anticausal; machine learning; causality aware; anticausal machine ... See more keywords
Simulation‐based education for novices: complex learning tasks promote reflective practice
Sign Up to like & getrecommendations! Published in 2019 at "Medical Education"
DOI: 10.1111/medu.13748
Abstract: Simulated clinical immersion (SCI), in which clinical situations are simulated in a realistic environment, safely and gradually exposes novices to complex problems. Given their limited experience, undergraduate students can potentially be quite overwhelmed by SCI… read more here.
Keywords: novices complex; education novices; based education; simulation based ... See more keywords
Average reward rates enable motivational transfer across independent reinforcement learning tasks
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Behavioral Neuroscience"
DOI: 10.3389/fnbeh.2022.1041566
Abstract: Outcomes and feedbacks on performance may influence behavior beyond the context in which it was received, yet it remains unclear what neurobehavioral mechanisms may account for such lingering influences on behavior. The average reward rate… read more here.
Keywords: reinforcement learning; reinforcement; task; average reward ... See more keywords
Coarse-Grained Neural Network Model of the Basal Ganglia to Simulate Reinforcement Learning Tasks
Sign Up to like & getrecommendations! Published in 2022 at "Brain Sciences"
DOI: 10.3390/brainsci12020262
Abstract: Computational models of the basal ganglia (BG) provide a mechanistic account of different phenomena observed during reinforcement learning tasks performed by healthy individuals, as well as by patients with various nervous or mental disorders. The… read more here.
Keywords: learning tasks; reinforcement learning; model; neural network ... See more keywords
Learner-Centred Learning Tasks in Higher Education: A Study on Perception among Students
Sign Up to like & getrecommendations! Published in 2021 at "Education Sciences"
DOI: 10.3390/educsci11050230
Abstract: Universities face the challenge of constantly improving the quality of higher education and changing the learning behaviour of students, from passive reactive learning to active self-regulated learning. Learner-centred, constructively designed learning tasks offer a great… read more here.
Keywords: learning tasks; learner centred; tasks higher; higher education ... See more keywords
TVGeAN: Tensor Visibility Graph-Enhanced Attention Network for Versatile Multivariant Time Series Learning Tasks
Sign Up to like & getrecommendations! Published in 2024 at "Mathematics"
DOI: 10.3390/math12213320
Abstract: This paper introduces Tensor Visibility Graph-enhanced Attention Networks (TVGeAN), a novel graph autoencoder model specifically designed for MTS learning tasks. The underlying approach of TVGeAN is to combine the power of complex networks in representing… read more here.
Keywords: learning tasks; time; attention; visibility graph ... See more keywords